large language model

UIUC_BioNLP at BioLaySumm: An Extract-then-Summarize Approach Augmented with Wikipedia Knowledge for Biomedical Lay Summarization ACL 2024 ULLME: A Unified Framework for Large Language Model Embeddings with Generation-Augmented Learning EMNLP 2024 ULMR: Unlearning Large Language Models via Negative Response and Model Parameter Average EMNLP 2024 UltraEval: A Lightweight Platform for Flexible and Comprehensive Evaluation for LLMs ACL 2024 UltraMedical: Building Specialized Generalists in Biomedicine NeurIPS 2024 ULTRA: Unleash LLMs’ Potential for Event Argument Extraction through Hierarchical Modeling and Pair-wise Self-Refinement ACL 2024 UMBCLU at SemEval-2024 Task 1: Semantic Textual Relatedness with and without machine translation SemEval 2024 UMUTeam at SemEval-2024 Task 4: Multimodal Identification of Persuasive Techniques in Memes through Large Language Models SemEval 2024 UMUTeam at SemEval-2024 Task 6: Leveraging Zero-Shot Learning for Detecting Hallucinations and Related Observable Overgeneration Mistakes SemEval 2024 Unbiased Watermark for Large Language Models ICLR 2024 Uncertainty Aware Learning for Language Model Alignment ACL 2024 Uncertainty Estimation in Large Language Models to Support Biodiversity Conservation NAACL 2024 Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in LLMs NeurIPS 2024 Uncertainty Resolution in Misinformation Detection EACL 2024 Unchosen Experts Can Contribute Too: Unleashing MoE Models’ Power by Self-Contrast NeurIPS 2024 Uncovering Differences in Persuasive Language in Russian versus English Wikipedia EMNLP 2024 Uncovering Limitations of Large Language Models in Information Seeking from Tables ACL 2024 Uncovering Safety Risks of Large Language Models through Concept Activation Vector NeurIPS 2024 Uncovering Stereotypes in Large Language Models: A Task Complexity-based Approach EACL 2024 Uncovering the Potential of ChatGPT for Discourse Analysis in Dialogue: An Empirical Study COLING 2024 Uncovering What Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly CVPR 2024 Understanding and Mitigating Language Confusion in LLMs EMNLP 2024 Understanding Faithfulness and Reasoning of Large Language Models on Plain Biomedical Summaries EMNLP 2024 Understanding In-Context Learning from Repetitions ICLR 2024 Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data NeurIPS 2024